Large-scale mRNA analysis of female skeletal muscles during 60 days of bed rest with and without exercise or dietary protein supplementation as countermeasures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microgravity has a dramatic impact on human physiology, illustrated in particular, with skeletal muscle impairment. A thorough understanding of the mechanisms leading to loss of muscle mass and structural disorders is necessary for defining efficient clinical and spaceflight countermeasures. We investigated the effects of long-term bed rest on the transcriptome of soleus (SOL) and vastus lateralis (VL) muscles in healthy women (BRC group, n = 8), and the potential beneficial impact of protein supplementation (BRN group, n = 8) and of a combined resistance and aerobic training (BRE group, n = 8). Gene expression profiles were obtained using a customized microarray containing 6,681 muscles-relevant genes. A two-class statistical analysis was applied on 2,103 genes with consolidated expression in BRC, BRN, and BRE groups. We identified 472 and 207 mRNAs whose expression was modified in SOL and VL from BRC group, respectively. Further clustering analysis, identifying relevant biological mechanisms and pathways, reported five main subclusters. Three are composed of upregulated mRNAs involved mainly in nucleic acid and protein metabolism, and two made up of downregulated transcripts encoding components involved in energy metabolism. Exercise countermeasure demonstrated drastic compensatory effects, decreasing the number of differentially expressed mRNAs by 89 and 96% in SOL and VL, respectively. In contrast, nutrition countermeasure had moderate effects and decreased the number of differentially-expressed transcripts by 40 and 25% in SOL and VL. Together, these data present a systematic, global and comprehensive view of the adaptive response of female muscle to long-term atrophy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it